〔Abstract〕 Objective To explore the risk factors for intracardiac thrombosis in dilated cardiomyopathy(DCM) patients and to construct, validate, and evaluate a nomogram prediction model based on these factors. Methods 88 patients diagnosed with DCM and complicated with intracardiac thrombus, and 544 patients without intracardiac thrombus were included. The participants were randomly divided into training and validation sets at a ratio of 7 ∶3. Using both univariate and multivariate Logistic regression analyses, independent risk factors for intracardiac thrombosis in DCM patients were identified. A nomogram prediction model was constructed using R software. The model's validity and performance were assessed using the receiver operating characteristic(ROC) curve, the Hosmer-Lemeshow goodness-of-fit test, calibration curve, and decision curve. Results The binary Logistic regression analysis showed that age, atrial fibrillation, left ventricular end-diastolic diameter(LVEDD), brain natriuretic peptide(BNP), and β-blockers were independently associated with intracardiac thrombosis in DCM patients. Based on these five factors, a nomogram was constructed and validated. The area under the ROC curve for the training set was 0.823(95%CI: 0.760～0.887) and 0.803(95%CI: 0.705～0.901) for the validation set, indicating a good discriminative ability. The Hosmer-Lemeshow test results for the calibration curve were(χ2=6.679,P=0.572) for the training set and(χ2=2.588,P=0.958) for the validation set, indicating a good fit between predicted and observed outcomes. The decision curve showed a high net clinical benefit in the threshold range of 0.05～0.92. Conclusion Based on age, atrial fibrillation, LVEDD, BNP, and β-blockers, the nomogram prediction model exhibits good discriminative and calibration abilities, and high clinical benefit. It can effectively guide clinicians in early intervention of risk factors, reducing the risk of intracardiac thrombosis in DCM patients.